Tag Archives: technology

Generative AI news discovery looks much more concentrated than other forms of access

Generative AI could in principle feature a great diversity of sources in output responding to news-related queries.

But do various generative AI products actually do this?

In early 2026, Roa Powell and Carsten Jung published a piece of research for the Institute for Public Policy suggesting maybe not – based on analysis of responses to a sample of 100 hypothetical UK news queries submitted to four different AI tools (ChatGPT, Perplexity, Gemini, and Google AI overview), they found that these tools draw “on a narrow range of prominent news brands”.

As a benchmark for interpreting their results, I have created the slide below.

The figures in red are my calculations of the Herfindahl–Hirschman Index (HHI) (a common measure of market concentration) for each of the four AI tools based on the share of reference that goes to each of the top ten news brands (as reported by Powell and Jung).

The figures in black are taken from this piece of work I did with Richard Fletcher included for comparison, namely similar HHI calculations based on historic data from the UK from 2017 for online news accessed directly, via search, news aggregators, or various kinds of social media, as well as, for further comparison, HHI figures for television viewing and weekly print newspaper circulation at the time.

The concentration of attention, with a few brands accounting for a very large share of reference, is far greater for the AI tools than any other form of access.

While the underlying data is not like-for-like comparison (the bulk of the 2017 data is based on passive tracking of actual UK users, the 2026 AI tool data is generated by prompting), I think the figures are still interesting and thought-provoking. (And not necessarily unique to the UK – Nikos Smyrnaios and Olivier Koch has published a piece of work, based on a somewhat different methodology, suggesting results for France that are also about the 2,000 bar for a highly concentrated market.)

It’s not just that Powell and Jung are right to stress that a narrow range of prominent news brands (some of whom have commercial deals with the AI companies) loom very large in AI output.

It is also that the concentration in question, measured here in terms of share of reference, is far, far greater than any of the different kinds of access we analyzed based on the 2017 data – even more concentrated than direct access, which itself was significantly more concentrated than any other kind of access at the time.

We already know that AI tools generate far fewer referrals than established platforms do – worrying enough for a multitude of publishers competing to connect with the public.

It also seems the (comparatively fewer) referrals they do drive are highly concentrated amongst a select few publishers, much more so than has been the case for search, social, or news aggregators.

(Underneath the topline, there is some diversity from tool to tool (just as we found different outlets doing well via different platforms), as Powell and Jung writes, their findings suggest “each AI tool prioritizing news brands in different ways, in each case foregrounding a distinct selection of news outlets compared with those that are currently most popular across the UK” – go read their report for more details.)

Misinformation often comes from the top (AKA “It’s the Elite, Stupid)

I wrote a piece for the Financial Times about why I think we need to focus squarely on this as we head into a big election year.

My (naively unworkable) working title when I submitted it was “It’s the elite, stupid: stop gaslighting the public about where consequential misinformation comes from”.

A few links below to evidence that has informed my view.

First, misinformation often comes from the top. Multiple studies have documented political actors’ role, e.g. the work of Yochai Benkler et al on network propaganda, Jonathan Ong and Ross Tapsell on fake news work models, Neelanjan Sircar’s work on disinformation as a type of state-sponsored violence and much more (I mean, look at a history book).

Second, what is crucial is not volume but influence. Hugo Mercier and others have pointed out, attempts at mass persuasion mostly fail!. But one thing that often influence people is elite cues from politicians they support.

Third, to state the obvious, some politicians sometimes weaponize false and misleading information for their own purposes. It’s easy to pin this on “populists” – there may be something to this – but it can come from establishment types too – Blair, Bush, Kennedy, Reagan, etc.

Fourth, faced with attempts to limit politicians’ ability to use misinformation, we see countless attacks on independent journalists, as well as on fact-checkers and researchers, plus attempts to legally prevent platforms from subjecting politicians to the same content moderation they apply to you or I.

Fifth, we don’t need to “forget” technology, as the FT headline suggests, but look at root causes – how political elites make use of tech, and how tech companies react to this use, sometimes treating them differently as a matter of policy, sometimes perhaps for pragmatic reasons.

In summary – misinformation often comes from the top, elite cues are more consequential than more misinformation added to what is already a vast ocean of content, populists may be particularly likely to use this for political purposes but they are not alone, and some politicians want to be allowed to act as they please. There is a lot of research on misinformation – if you are interested in more, great and warmly recommended resources include the “Critical Disinformation Studies” syllabus from CITAP, Brendan Nyhan’s “Political Misinformation” syllabus as well as (both of these are pretty US-focused) for example the edited volume “Disinformation in the Global South” for a wider view.